Improvement of DBR routing protocol in underwater wireless sensor networks using fuzzy logic and bloom filter.

Routing protocols for underwater wireless sensor networks (UWSN) and underwater Internet of Things (IoT_UWSN) networks have expanded significantly. DBR routing protocol is one of the most critical routing protocols in UWSNs. In this routing protocol, the energy consumption of the nodes, the rate of loss of sent packets, and the rate of drop of routing packets due to node shutdown have created significant challenges. For this purpose, in a new scenario called FB-DBR, clustering is performed, and fuzzy logic and bloom filter are used in each cluster's new routing protocol in underwater wireless sensor networks. Due to the fuzzy nature of the parameters used in DBR, better results are obtained and bloom filters are used in routing tables to compensate for the deceleration. as the average number of accesses to routing table entries, dead nodes, Number of Packets Sent to Base Station (BS), Number of Packets Received at BS, Packet Dropped, and Remaining Energy has improved significantly.

Algorithm for wireless sensor networks in ginseng field in precision agriculture.

In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng.

Blood glucose related adverse drug reaction of antitumor monoclonal antibodies: a retrospective analysis using Vigibase

Abstract On the increasing prevalence of using mAbs (monoclonal antibodies) in cancer therapy and the severe risk of hyperglycemia, we aimed to analyze the main clinical ADRs of mAbs, with a focus on adverse hyperglycemic events associated with currently clinically used mAbs. mAbs as well as target information were selected from Martinadale book and published articles. Drug approving information was collected from each government website, and ADR statistic data were collected from VigibaseR, comparing with Adverse Event Reporting System of US FDA. Top 10 mAbs were classified within listing in total ADR records, ADRs per year, hyperglycemic ADR records. Vigibase data were updated onto 15 Feb 2019. 20 mAbs were analyzed with 263217 ADR reports, wherein 16751 records on Metabolism and nutrition disorders and 1444 records on Glucose metabolism disorders. The geographic, age, gender distributions and annual ADR report numbers were listed respectively. Of the top 10, Rituximab, Bevacizumab and Nivolumab were on the top 3 in total ADR record and hyperglycemic record. Top 3 record results were similar in Vigibase and FDA database. It is of increasing importance for clinicians to be aware of early detection, patient management, or drug selection strategies when using mAbs, particularly within the high glycemic risk-reported mAbs, to improve the efficacy and tolerability of mAbs regiment and optimize patient outcomes.

Electromagnetic compatibility issues in hybrid wired and wireless industrial networks.

Industrial networks are currently the only communication means designed for real-time systems used in industry. Networked control systems (NCS) are still important and commonly used type of such systems operating on shop floor. As a computerized node of NCS, a programmable logic controller (PLC) is usually used. In most cases, contemporary devices of such kind are equipped with more than one network interface of various types. Typically, only one interface is activated in NCS. Sometimes, the other is used for communication between NCS and supervisory systems. Occasionally, it is additionally involved in the data transmission in the factory IT systems. In general, however, using a single network interface is a more common solution. In this paper, the mutual utilization of more than one interface is discussed in order to back up the NCS network and to manage the node-related traffic within the scope of higher level services. The question of dependability of such a system from the electromagnetic compatibility point of view is discussed. The example is provided based on Profinet via wired and wireless connection.

TrustBlock: An adaptive trust evaluation of SDN network nodes based on double-layer blockchain.

The data layer devices in the Software Defined Network (SDN) play an important role in packet forwarding. However, whether the forwarding task can be efficiently completed by the node has not attracted enough attention. A method called TrustBlock is proposed in this paper, which introduces trust as a security attribute in SDN routing planning. Besides, in order to enhance the integrity and controllability of trust evaluation, the double-layer blockchain architecture is established. In the first layer, the behavior data of the node is recorded, and then the trust calculation is performed in the second layer. In the evaluation model, nodes' trust is calculated from three aspects: direct trust, indirect trust and historical trust. Firstly, from the perspective of security, blockchain is used to achieve identity authentication of nodes, after that, from the perspective of reliability, the forwarding status is used to calculate the trust value. Secondly, consensus algorithm is used to filter malicious recommendation trust value and prevent colluding attacks. Finally, the adaptive historical trust weight is designed to prevent the periodic attack. In this paper, the entropy method is used to determine the weight of each evaluation attribute, which can avoid the problem that the subjective judgment method is not adaptable to the weight setting. Simulation results show that the detection rate of the TrustBlock is up to 98.89%, which means this model can effectively identify the abnormal nodes in SDN. Moreover, it is attractive in terms of integrity and controllability.

Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture.

The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV-WSN-IoT approach increases the performances in both precision agriculture and ecological agriculture.

Starviewer and its comparison with other open-source DICOM viewers using a novel hierarchical evaluation framework.

METHODS: The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible. RESULTS: Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8). CONCLUSIONS: Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models.

A Comprehensive Data Gathering Network Architecture in Large-Scale Visual Sensor Networks.

The fundamental utility of the Large-Scale Visual Sensor Networks (LVSNs) is to monitor specified events and to transmit the detected information back to the sink for achieving the data aggregation purpose. However, the events of interest are usually not uniformly distributed but frequently detected in certain regions in real-world applications. It implies that when the events frequently picked up by the sensors in the same region, the transmission load of LVSNs is unbalanced and potentially cause the energy hole problem. To overcome this kind of problem for network lifetime, a Comprehensive Visual Data Gathering Network Architecture (CDNA), which is the first comparatively integrated architecture for LVSNs is designed in this paper. In CDNA, a novel α-hull based event location algorithm, which is oriented from the geometric model of α-hull, is designed for accurately and efficiently detect the location of the event. In addition, the Chi-Square distribution event-driven gradient deployment method is proposed to reduce the unbalanced energy consumption for alleviating energy hole problem. Moreover, an energy hole repairing method containing an efficient data gathering tree and a movement algorithm is proposed to ensure the efficiency of transmitting and solving the energy hole problem. Simulations are made for examining the performance of the proposed architecture. The simulation results indicate that the performance of CDNA is better than the previous algorithms in the realistic LVSN environment, such as the significant improvement of the network lifetime.

Smart Buildings IoT Networks Accuracy Evolution Prediction to Improve Their Reliability Using a Lotka-Volterra Ecosystem Model.

Internet of Things (IoT) is the paradigm that has largely contributed to the development of smart buildings in our society. This technology makes it possible to monitor all aspects of the smart building and to improve its operation. One of the main challenges encountered by IoT networks is that the the data they collect may be unreliable since IoT devices can lose accuracy for several reasons (sensor wear, sensor aging, poorly constructed buildings, etc.). The aim of our work is to study the evolution of IoT networks over time in smart buildings. The hypothesis we have tested is that, by amplifying the Lotka-Volterra equations as a community of living organisms (an ecosystem model), the reliability of the system and its components can be predicted. This model comprises a set of differential equations that describe the relationship between an IoT network and multiple IoT devices. Based on the Lotka-Volterra model, in this article, we propose a model in which the predators are the non-precision IoT devices and the prey are the precision IoT devices. Furthermore, a third species is introduced, the maintenance staff, which will impact the interaction between both species, helping the prey to survive within the ecosystem. This is the first Lotka-Volterra model that is applied in the field of IoT. Our work establishes a proof of concept in the field and opens a wide spectrum of applications for biology models to be applied in IoT.

Priority based health data monitoring with IEEE 802.11af technology in wireless medical sensor networks.

In this work, the IEEE 802.11af technology-based wireless sensor network for health data monitoring with priority classes is proposed. In IEEE 802.11af technology, a White Space Device (WSD), a Station (STA), and an Access Point (AP) communicate through television white spectrum opportunistically without causing any harmful interference to licensed` services. In the proposed network; WSDs, STA, and AP employ Frequency Division Multiple Access (FDMA) technique with the aim of communicating through the white space spectrum determined by White Space Map (WSM). WSD collects health data such as body temperature and blood pressure from an implant or on-body sensors. The priority class is determined according to the emergency of a patient as red, yellow, and green. After obtaining the analytical model of the proposed network, the simulation model is carried out using Riverbed Modeler. The graphical results prove the validity and applicability of the proposed network in terms of delay (0.17 s) and energy consumption (4.7 mJ/s) without any spectrum cost for priority-based health data monitoring. Graphical abstract Cognitive radio based IEEE 802.11af environment for priority based health data monitoring.

VLC, OCC, IR and LiFi Reliable Optical Wireless Technologies to be Embedded in Medical Facilities and Medical Devices.

New, emerging technologies, transform every day our life and have direct consequence on our health and well-being. More and more wearable medical devices (MD) with wireless communication technologies embedded are being developed by innovative academic community and companies. Optical wireless communication (OWC) consisting of Visible Light Communication (VLC), infrared (IR), Optical Camera Communication (OCC) and Light Fidelity (LiFi) along with the conventional Radio Frequency (RF) wireless communication are suitable technologies to be used for hybrid Wireless Integrated Medical Assistance Systems (WIMAS). The WIMAS addressed in this paper consists of two Wireless Medical Body Area Networks (WMBAN) (an insulin wearable kit and an ECG test device with VLC/OCC are considered) and an Emergency Remote Medical Assistance (ERMA) with LiFi technology embedded. Using RF in medical facilities is subject of strict regulations due to interferences with other RF medical devices, negative effects on human health and lack of security. VLC and OCC are suitable to be embedded in MDs in order to be used by the patients with wearable WMBAN. Research on IR transdermal communication for implantable MDs has also been demonstrated as feasible and both VLC and OCC have promising future, as well. On the other hand, LiFi technology, recently deployed on the market, is mature enough to be integrated in the ERMA system addressed here.

APPLICATION OF TIME-AVERAGED AND INTEGRAL-BASED MEASURE FOR MEASUREMENT RESULTS VARIABILITY REDUCTION IN GSM/DCS/UMTS SYSTEMS.

Since EMF levels from wireless telecommunication networks are non-stationary and exhibit large temporal variations, the use of continuous measurements during extended periods (preferably 24 h or longer) with a data-logging system is required. Because of the short-term variations of E field, the 6-min measurements and 6-min averaged results to obtain the mean level strength at a given place appear to be dependent on the time of measurements during the day. This paper presents a new (integral-based) measure to evaluate electromagnetic exposure. The new measure is a pure physical descriptor of the amount of exposed energy density (a parameter accumulated from instantaneous power density values in time). To confirm previous observations, continuous measurements with personal exposure metre were recorded 24 h a day for two weeks at every location in urban area, 14 different locations in total. Additionally, to check temporal variations and repeatability of exposure assessment, a week of prolonged measurements was taken 6 months later, making in total three weeks of measurements at 2 locations. Day-to-day repeatability of RF-EMF exposure was analysed through the time-averaged and integral-based measure. The analysis is based on approximately 5.1 million data samples (1.7 million for each band). The ratio between the maximum and minimum instantaneous (maximum and minimum 6-min averaged) E field values during the day could reach up to 25 dB (20 dB). Therefore, great variability in the results may occur. By applying the 24 h time-averaged and integral-based measure on a 24 h data set of measurements, the variability of daily exposure could stay within ±20% of the week mean level obtained either with the time-averaged or integral-based measure. Both, the time-averaged E field and integral-based power density exposures of the general public in all locations were found to be well below the general public exposure limits of the ICNIRP guidelines.

DAD-match; Security technique to prevent denial of service attack on duplicate address detection process in IPv6 link-local network.

An efficiently unlimited address space is provided by Internet Protocol version 6 (IPv6). It aims to accommodate thousands of hundreds of unique devices on a similar link. This can be achieved through the Duplicate Address Detection (DAD) process. It is considered one of the core IPv6 network's functions. It is implemented to make sure that IP addresses do not conflict with each other on the same link. However, IPv6 design's functions are exposed to security threats like the DAD process, which is vulnerable to Denial of Service (DoS) attack. Such a threat prevents the host from configuring its IP address by responding to each Neighbor Solicitation (NS) through fake Neighbor Advertisement (NA). Various mechanisms have been proposed to secure the IPv6 DAD procedure. The proposed mechanisms, however, suffer from complexity, high processing time, and the consumption of more resources. The experiments-based findings revealed that all the existing mechanisms had failed to secure the IPv6 DAD process. Therefore, DAD-match security technique is proposed in this study to efficiently secure the DAD process consuming less processing time. DAD-match is built based on SHA-3 to hide the exchange tentative IP among hosts throughout the process of DAD in an IPv6 link-local network. The obtained experimental results demonstrated that the DAD-match security technique achieved less processing time compared with the existing mechanisms as it can resist a range of different threats like collision and brute-force attacks. The findings concluded that the DAD-match technique effectively prevents the DoS attack during the DAD process. The DAD-match technique is implemented on a small area IPv6 network; hence, the author future work is to implement and test the DAD-match technique on a large area IPv6 network.

Video loss prediction model in wireless networks.

This work discusses video communications over wireless networks (IEEE 802.11ac standard). The videos are in three different resolutions: 720p, 1080p, and 2160p. It is essential to study the performance of these media in access technologies to enhance the current coding and communications techniques. This study sets out a video quality prediction model that includes the different resolutions that are based on wireless network terms and conditions, an approach that has not previously been adopted in the literature. The model involves obtaining Service and Experience Quality Metrics, such as PSNR (Peak Signal-to-Noise Ratio) and packet loss. This article outlines a methodology and mathematical model for video quality loss in the wireless network from simulated data and its accuracy is ensured through the use of performance metrics (RMSE and Standard Deviation). The methodology is based on two mathematical functions, (logarithmic and exponential), and their parameters are defined by linear regression. The model obtained RMSE values and standard deviation of 2.32 dB and 2.2 dB for the predicted values, respectively. The results should lead to a CODEC (Coder-Decoder) improvement and contribute to a better wireless networks design.

The Design of an Energy Harvesting Wireless Sensor Node for Tracking Pink Iguanas.

The design of wireless sensor nodes for animal tracking is a multidisciplinary activity that presents several research challenges both from a technical and a biological point of view. A monitoring device has to be designed accounting for all system requirements including the specific characteristics of animals and environment. In this work we present some aspects of the design of a wireless sensor node to track and monitor the pink iguana of the Galápagos: a recently discovered species living in remote locations at the Galápagos Islands. The few individuals of this species live in a relatively small area that lacks of any available communication infrastructure. We present and discuss the energy harvesting architecture and the related energy management logic. We also discuss the impact of packaging on the sensor performance and the consequences of the limited available energy on the GPS tracking.

Power-system protection device with IoT-based support for integration in smart environments.

This paper proposes a power-system protection device designed to be integrated in smart environments based on Internet-of-Things technologies. The proposed system enhances electrical safety by fast disconnection of the power supply in case of fault events like leakage current, electrical arc, overcurrent or overvoltage and has been designed with the goal to be integrated in smart environments like smart homes or smart cities for protecting the electrical equipment. The system also enables real-time monitoring and notification events through an advanced communication interface using a data concentrator architecture. This paper provides an extended description of the proposed system's design and implementation, as well as the experimental validation results.

Support for Employees with ASD in the Workplace Using a Bluetooth Skin Resistance Sensor⁻A Preliminary Study.

The application of a Bluetooth skin resistance sensor in assisting people with Autism Spectrum Disorders (ASD), in their day-to-day work, is presented in this paper. The design and construction of the device are discussed. The authors have considered the best placement of the sensor, on the body, to gain the most accurate readings of user stress levels, under various conditions. Trial tests were performed on a group of sixteen people to verify the correct functioning of the device. Resistance levels were compared to those from the reference system. The placement of the sensor has also been determined, based on wearer convenience. With the Bluetooth Low Energy block, users can be notified immediately about their abnormal stress levels via a smartphone application. This can help people with ASD, and those who work with them, to facilitate stress control and make necessary adjustments to their work environment.

Spatial-temporal modeling of background radiation using mobile sensor networks.

Modeling of background radiation for the urban environment plays an important role in homeland security. However, background radiation is difficult to assess due to its spatial-temporal fluctuations caused by the variation in soil composition, building materials, and weather patterns etc. To address the challenge of background radiation modeling, we developed a mobile sensor network to continuously monitor the background radiation; we also proposed a maximum likelihood estimation algorithm to decouple and estimate the background's spatial distribution and temporal fluctuation. Experimental results demonstrated how this background radiation monitoring system accurately recognized high background regions in the experimental area, and successfully captured temporal fluctuation trends of background radiation during rains. Our system provides an efficient solution to model the temporal fluctuation and spatial distribution of background radiation.

Cross-layer model design in wireless ad hoc networks for the Internet of Things.

Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods.

WarpEngine, a Flexible Platform for Distributed Computing Implemented in the VEGA Program and Specially Targeted for Virtual Screening Studies.

The manuscript describes WarpEngine, a novel platform implemented within the VEGA ZZ suite of software for performing distributed simulations both in local and wide area networks. Despite being tailored for structure-based virtual screening campaigns, WarpEngine possesses the required flexibility to carry out distributed calculations utilizing various pieces of software, which can be easily encapsulated within this platform without changing their source codes. WarpEngine takes advantages of all cheminformatics features implemented in the VEGA ZZ program as well as of its largely customizable scripting architecture thus allowing an efficient distribution of various time-demanding simulations. To offer an example of the WarpEngine potentials, the manuscript includes a set of virtual screening campaigns based on the ACE data set of the DUD-E collections using PLANTS as the docking application. Benchmarking analyses revealed a satisfactory linearity of the WarpEngine performances, the speed-up values being roughly equal to the number of utilized cores. Again, the computed scalability values emphasized that a vast majority (i.e., >90%) of the performed simulations benefit from the distributed platform presented here. WarpEngine can be freely downloaded along with the VEGA ZZ program at www.vegazz.net .